Gaskill Christopher S, Awan Jordan A, Watts Christopher R, Awan Shaheen N
Department of Communication Science and Disorders, University of Montevallo, Montevallo, Alabama.
Brandeis University, Waltham, Massachusetts.
J Voice. 2017 Mar;31(2):218-228. doi: 10.1016/j.jvoice.2016.04.016. Epub 2016 May 27.
Intermittent dysphonia within an utterance is common, but presents difficulty for both perceptual and objective voice evaluation. This study examined the ability of measures from the within-sample cepstral peak prominence (CPP) distribution to differentiate normal voices from intermittently and consistently dysphonic voices.
Exploratory design.
Sixty samples of the sentence "We were away a year ago" were classified as normal, intermittently dysphonic, or consistently dysphonic by four judges. Measures of CPP within each sample were obtained, and further analysis with examined CPP distribution variability and patterns of CPP outliers.
Whereas the mean CPP was the strongest single discriminator among the three voice types, the normal and intermittent dysphonia groups were not significantly different on CPP distribution skewness and measures of CPP distribution outliers. Both the normal and intermittently dysphonic voices differed significantly from the consistently dysphonic samples on these variables. A combination of measures of the CPP distribution was effective for a linear prediction of percent dysphonia duration for the speech samples (r = 0.825; rho = 0.81). The CPP standard deviation significantly improved the use of the mean CPP in discriminant function analyses and also the classification of the intermittently dysphonic voices.
Auditory-perceptual judgment of dysphonic segments and the typically robust acoustic measurement of mean CPP are both ineffective for classifying intermittently dysphonic voices. However, dysphonia duration may be effectively predicted via measures of the CPP distribution, and acoustic classification of dysphonic voice types via cepstral methods may be improved with an analysis of the CPP distribution across an utterance.
发声过程中出现间歇性发音障碍很常见，但对感知性和客观性嗓音评估都存在困难。本研究考察了样本内谐波峰值突出度（CPP）分布测量指标区分正常嗓音与间歇性和持续性发音障碍嗓音的能力。
探索性设计。
由四名评判员将60个“We were away a year ago”句子样本分类为正常、间歇性发音障碍或持续性发音障碍。获取每个样本的CPP测量指标，并进一步分析CPP分布变异性和CPP离群值模式。
虽然平均CPP是三种嗓音类型中最强的单一判别指标，但正常嗓音组和间歇性发音障碍组在CPP分布偏度和CPP分布离群值测量方面无显著差异。在这些变量上，正常嗓音和间歇性发音障碍嗓音与持续性发音障碍样本均有显著差异。CPP分布测量指标的组合对语音样本的发音障碍持续时间百分比进行线性预测有效（r = 0.825；rho = 0.81）。CPP标准差在判别函数分析中显著改善了平均CPP的使用效果，也提高了间歇性发音障碍嗓音的分类准确率。
对发音障碍片段的听觉感知判断以及通常可靠的平均CPP声学测量指标，在对间歇性发音障碍嗓音进行分类时均无效。然而，通过CPP分布测量指标可以有效预测发音障碍持续时间，并且通过对整个发声过程中CPP分布的分析，基于谐波方法对发音障碍嗓音类型进行声学分类可能会得到改善。
